Optimum filter banks for signal decomposition and its application in adaptive echo cancellation

The application of multirate filter banks in echo cancellation is investigated. The multiresolution algorithm is used to decompose the received sampling sequence into a number of components, and then, an adaptive algorithm is applied to cancel the echo in the received signal. In this paper, the performance of this method is discussed, from which optimal conditions for echo cancellation are established for the design of wavelet packet multiresolution decomposition. An efficient algorithm for designing such a set of optimal discrete filter banks is developed. The cases of optimal in-band and adjacent-band adaptive filtering are examined. Experimental results showed that the use of optimally designed multiresolution filter banks coupled with in-band or adjacent-band adaptive filtering is much more effective than the employment of commonly used wavelet filter banks. Furthermore, the use of the adjacent-band adaptive filtering algorithm has superior performance compared with that of the in-band filtering.